Article ; Online: Robust expansion of phylogeny for fast-growing genome sequence data.
2024 Volume 20, Issue 2, Page(s) e1011871
Abstract: Massive sequencing of SARS-CoV-2 genomes has urged novel methods that employ existing phylogenies to add new samples efficiently instead of de novo inference. 'TIPars' was developed for such challenge integrating parsimony analysis with pre-computed ... ...
| Abstract | Massive sequencing of SARS-CoV-2 genomes has urged novel methods that employ existing phylogenies to add new samples efficiently instead of de novo inference. 'TIPars' was developed for such challenge integrating parsimony analysis with pre-computed ancestral sequences. It took about 21 seconds to insert 100 SARS-CoV-2 genomes into a 100k-taxa reference tree using 1.4 gigabytes. Benchmarking on four datasets, TIPars achieved the highest accuracy for phylogenies of moderately similar sequences. For highly similar and divergent scenarios, fully parsimony-based and likelihood-based phylogenetic placement methods performed the best respectively while TIPars was the second best. TIPars accomplished efficient and accurate expansion of phylogenies of both similar and divergent sequences, which would have broad biological applications beyond SARS-CoV-2. TIPars is accessible from https://tipars.hku.hk/ and source codes are available at https://github.com/id-bioinfo/TIPars. |
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| MeSH term(s) | Phylogeny ; Likelihood Functions ; Genome ; Software ; SARS-CoV-2/genetics |
| Language | English |
| Publishing date | 2024-02-08 |
| Publishing country | United States |
| Document type | Journal Article |
| ZDB-ID | 2193340-6 |
| ISSN | 1553-7358 ; 1553-734X |
| ISSN (online) | 1553-7358 |
| ISSN | 1553-734X |
| DOI | 10.1371/journal.pcbi.1011871 |
| Database | MEDical Literature Analysis and Retrieval System OnLINE |
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